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Bonus Focus - Microlearning: Separating the Science from the Fiction

By Steven Just, Ed.D.

Without doubt, microlearning has an important place as part of any life science company’s training strategy. But as with many new training methodologies it suffers from over-hype. If we are to understand how to use it effectively, we must first separate the science from the fiction.

And what is the cause of this demise in our attention span? Smartphones of course. Apparently some time beginning around 2007, when the first iPhone was introduced, our brains started to rewire themselves.

And, according to some, what is the solution to this problem? Replace traditional courses with microlearning. To teach millennials you need to deliver short bursts of information tailored to their rewired brains. Or, as one article put it:
Millennials love to learn, but traditional workplace training often does not reflect their distinctive learning style.

The Science
Hype of any sort generally grows from a kernel of truth. So it is true that all humans (not just millennials) have limited capacity for absorbing and storing new knowledge. (But it is not true that millennials have invented a new “learning style.”) To understand how microlearning addresses these human limitations, and how and when to use it, you first need to understand how we learn and store new knowledge.

Figure 1 shows the three parts to human memory:

Sensory memory includes all of the inputs (visual, auditory, haptic) that you are constantly receiving from your environment every moment of the day. Naturally, most of this is unimportant and is quickly discarded; otherwise your brain would be rapidly overloaded with data.

Working memory is where you process important information and is key for learning. Unfortunately working memory is very limited. Cognitive scientists used to believe that we could hold approximately seven discrete items in working memory at once (this is known as Miller’s Magic Number) but now most scientists believe the number is actually less, perhaps four or five.

So, what we really want to remember we need to transfer from working memory to long-term memory because working memory is not only limited in capacity but also in duration – maybe a minute or two.

To be sure it is possible to convey some discrete knowledge in short-term learning nuggets (e.g. a revised HR policy), but most life science training is complex and relies on the building of long-term schema for understanding. For example, if we were learning about human memory we might form a schema that looks like this:

But long-term memory itself is fragile. Our brains are not like permanent computer storage. In fact, if we don’t reinforce long-term memory periodically we will forget in a matter of hours or days what we want to remember. To reinforce knowledge, we must recall it from long-term into working memory, process it and then re-store it back into long term memory. This process is known as re-encoding.

So this is where microlearning fits in: Not generally for the initial learning experience, which requires in-depth treatment to enable learners to form structured schema, but for review and reinforcement days, weeks and months after a formal learning experience, so that the knowledge is not lost.

We’ve known for quite a while that our capacity to process new knowledge is limited and that for effective learning to occur it needs to be reinforced. So why is microlearning having its moment now? Well, because of those ubiquitous mobile devices. They may not be rewiring our brains but they are excellent platforms for delivering short reinforcement learning nuggets to your learners.

So, despite the hype, microlearning will not replace formal, structured learning. But every life science company should incorporate microlearning into its continuous learning strategy to promote long-term learning retention.